Timeroom: Fall 2018

Displaying 211 - 220 of 1112 Results for: Level = All Graduate
Durham   Engineering&Physical Sciences :: Computer Science

CS 998 (01) - Independent Study

Credits: 1.0 to 6.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Letter Grading
CRN: 10844
Section above not available for web registration; Check with dept for details.
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 999 (01) - Doctoral Research

Credits: 0.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Graduate Credit/Fail grading
CRN: 10436
Cr/F.
Section above not available for web registration; Check with dept for details.
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 999 (17) - Doctoral Research

Credits: 0.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Graduate Credit/Fail grading
Class Size:   1  
CRN: 16258
Cr/F.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 Hours Arranged TBA
Durham   Graduate School :: Analytics

DATA 800 (1ON) - Introduction to Applied Analytic Statistics

Intro: Applied Analytic Stats

Credits: 3.0
Term: Fall 2018 - E-term I (08/13/2018 - 10/05/2018)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 17453
This course is designed to give students a solid understanding of the experience in probability, and inferential statistics. The course provides a foundational understanding of statistical concepts and tools required for decision making in a data science, business, research or policy setting. The course uses case studies and requires extensive use of statistical software.
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
8/13/2018 10/5/2018 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 812 (01) - Health Analytics

Credits: 3.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 16174
This course introduces students to the field of health analytics and data science. It expands upon introductory statisitcal and data manipulation methods to include data mining, predictive analytics, cluster analysis, trend and pattern recognition, and data visualization. It couples data skills with interpretive and communication skills. Students will also be exposed to basic statistical programming. There will be a graduate component of the course (812) where students will work on advanced concepts and complete a separate culminating project.
Equivalent(s): HMP 812
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 MW 2:10pm - 3:30pm PETT 114
8/27/2018 12/10/2018 T 3:40pm - 5:00pm HEW 301
Durham   Graduate School :: Analytics

DATA 820 (1ON) - Programming for Data Science

Credits: 3.0
Term: Fall 2018 - E-term I (08/13/2018 - 10/05/2018)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 17452
In this class, students will build their foundational toolbox in data science: upon completion, students will be able to use the computer from the command line; practice version control with GIT & GitHub; gain a mastery of programming in Python; data wrangling with Python and perform an exploratory data analysis (EDA) in Python. All learning objectives are achieved through active application of these techniques to real world datasets. Pre- or Coreq: DATA 800.
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
8/13/2018 10/5/2018 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 821 (1ON) - Data Architecture

Credits: 3.0
Term: Fall 2018 - E-term II (10/15/2018 - 12/11/2018)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 17454
In this class, students will learn the foundations of databases and large datasets: upon completion, students will be able to explore out-of-ram datasets though traditional SQL databases and NoSQL databases. Students will also be introduced to distributed computing. All learning objectives are achieved through active application of these techniques to world datasets. Prereq: DATA 800; DATA 820.
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
10/15/2018 12/11/2018 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 822 (1ON) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Credits: 3.0
Term: Fall 2018 - E-term II (10/15/2018 - 12/11/2018)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 17451
In this class, students will learn foundations of practical machine learning: upon completion, students will be able to understand and apply supervised and unsupervised learning in Python to build predictive models on real world datasets. Techniques covered include (but not limited to): preprocessing, dimensionality reduction, clustering, feature engineering and model evaluation. Models covered include: generalized linear models, tree-based models, bayesian models, support vector machines, and neural networks. All learning objectives are achieved through active application of these techniques to real world datasets. Prereq: DATA 800; DATA 820 Pre- or Coreq: DATA 821.
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
10/15/2018 12/11/2018 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 896 (01) - Self-Designed Analytics Lab I

Analytics Lab I

Credits: 3.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 14773
This is the first of a two course self-designed thesis sequence offered under the master's of science degree in analytics. The nature of the class will be applied learning directly around a student directed analytic thesis project. Students will have a choice of either bringing an analytical problem of their interest or one assigned by the instructor out of the ongoing projects in the lab. The student chosen problem will be vetted thoroughly and a decision will be made based on the depth of the proposed data management and analysis proposed submitted in the proposal. Once approved by the committee, the students will collect, clean, merge and create readable analytical files for the project and write a formal 2000+ words report on the data mining part of the project. Prereq: DATA 803 and permission.
Only listed majors in section: ANALYTICS, ANALYTICS CERT
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 Hours Arranged TBA
Durham   Graduate School :: Analytics

DATA 900 (01) - Data Architecture

Credits: 3.0
Term: Fall 2018 - Full Term (08/27/2018 - 12/10/2018)
Grade Mode: Letter Grading
Class Size:   44  
CRN: 14330
The module-driven course builds off previous introductory analytics coursework and exposes students to advanced level concepts and techniques with respect to big data, data management, architecture, mining, privacy, and security concerns. Prereq: DATA 800.
Only listed majors in section: ANALYTICS, ANALYTICS CERT
Instructors: STAFF
Start Date End Date Days Time Location
8/27/2018 12/10/2018 Hours Arranged PBLANE 216